Identification of potential biomarkers of venous thromboembolism in patients with COVID-19 via an integrated bioinformatic-based study

Abstract

Abstract Background As a result of the COVID-19 pandemic, venous and arterial thromboembolic events have increased dramatically in many patients. This study aimed to identify the potential biomarkers for COVID-19-associated venous thromboembolism (VTE). Methods The datasets about COVID-19 and VTE were downloaded from the Gene Expression Omnibus (GEO) dataset. Weighted gene co-expression network analysis (WGCNA) was conducted to identify the most critical module associated with the clinic results. The intersection of common modules was processed for further enrichment analysis. The hub genes were identified by combining the differentially expressed genes (DEGs) of VTEs and common module genes. Then, the final diagnostic value for VTE was verified through bioinformatics algorithms. Results As many as 78 common critical genes were summarized by the intersection of the most positive and negative modules of COVID-19 and VTE. These genes were mainly enriched in coronavirus disease, fluid shear stress and atherosclerosis, ribosome, NF-kappa B, and TNF signalling pathways. Four critical genes including GZMA, BCL2A1, CD52, and RANSE2 were selected by performing the intersection analysis with the DEGs in VTE. All these genes were found to be increased in VTE samples in GSE19151 and achieved a good diagnostic value with a relative proper area under the curve (AUC). Conclusions Our study found that similar changes occurred in COVID-19 and VTE. GZMA, BCL2A1, CD52, and RANSE2 can be utilized as potential diagnostic markers for COVID-19-related VTE. This study may offer new opportunities for the detection and prevention of COVID-19-induced hypercoagulable state and VTE.